To determine the reliability of the linear model based on the information about the residual plot, we can consider the main principles of analyzing residuals.
- Residuals are the differences between observed and predicted values:
- If the residuals are randomly distributed around zero, it indicates that the linear model is appropriate for the data.
- If there is a distinct pattern in the residuals, it suggests that the linear model is not a good fit, and a different model may be more appropriate.
Based on this understanding, the appropriate response is:
"The given residual plot clearly has a pattern. Therefore, the linear model is not reliable and will not provide accurate predictions for the original data."
This response indicates that the presence of a pattern in the residuals suggests the linear model does not adequately capture the relationships in the data.